Probe speed data are widely used to calculate performance measures for quantifying state-wide traffic conditions. Estimation of the accurate performance measures requires adequate speed data observations. However, probe vehicles reporting the speed data may not be available all the time on each road segment. Agencies need to develop a good understanding of the adequacy of these reported data before using them in different transportation applications. This study attempts to systematically assess the quality of the probe data by proposing a method, which determines the minimum sample rate for checking data adequacy. The minimum sample rate is defined as the minimum required speed data for a segment ensuring the speed estimates within a defined error range. The proposed method adopts a bootstrapping approach to determine the minimum sample rate within a pre-defined acceptance level. After applying the method to the speed data, the results from the analysis show a minimum sample rate of 10% for Kentucky’s roads. This cut-off value for Kentucky’s roads helps to identify the segments where the availability is greater than the minimum sample rate. This study also shows two applications of the minimum sample rates resulted from the bootstrapping. Firstly, the results are utilized to identify the geometric and operational factors that contribute to the minimum sample rate of a facility. Using random forests regression model as a tool, functional class, section length, and speed limit are found to be the significant variables for uninterrupted facility. Contrarily, for interrupted facility, signal density, section length, speed limit, and intersection density are the significant variables. Lastly, the speed data associated with the segments are applied to improve Free Flow Speed estimation by the traditional model.

Over the past few decades, the value and weight of freight shipments have grown steadily in both developed and developing countries. A recent statistic in the U.S. reveals that weight of shipments increased from 18,879 to 19,662 million tons between 2007 and 2012 (1). It is also expected that this amount will increase to 28,520 million tons by 2040 (1). It is worth mentioning that 67 percent of shipments are shipped by truck mode in 2012. The monetary value of freight is expected to escalate even faster than weight. This value is estimated to rise from US$ 882 per ton in 2007 to US$ 1,377 per ton in 2040. As a result, freight transportation management and modeling has aroused the interest of both public sector and groups of firms to improve the efficiency of the business operations. Traffic assignment plays a central role in the current freight modeling, and freight route analysis is of fundamental importance in understanding the truck flows explicitly. In the first part of this thesis, large streams of truck-GPS data from the American Transportation Research Institute (ATRI) are cleaned, processed, and analyzed using easy to implement and practical procedures to study the diversity of observed truck routes between a given origin-destination (OD) pair. This is because, for any given OD pair, the analyst could observe and compare the route choices of a large number of trips, as opposed to observing only one or a few trips. Doing so helps in quantifying the number of different routes taken by trucks between an OD pair and paves the way for a systematic analysis of the “diversity” in route choices between any OD pair. This thesis develops methods to measure the diversity of routes between a given OD pair and identifies unique routes used between the given OD pair. From a practical standpoint, such analysis of the diversity in observed route choices helps in improving the existing route choice set generation algorithms. In the second part of the thesis, the methodologies developed in the first part are implemented in an FDOT sponsored project entitled “GPS Data for Truck-Route Choice Analysis of Port Everglades Petroleum Commodity Flows”. This project aims to use truck-GPS data from ATRI to derive petroleum tanker trucks’ travel path (or route) information, describing the routes that the tanker trucks take to travel from Port Everglades to their final delivery points.